{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Excel Automation\n",
    "\n",
    "In this example we perform a multitude of Excel operations as an illustration"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initializing Automagica\n",
    "\n",
    "The first step in building a script with Automagica is to import all the Automagica activities."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "from automagica import *"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Starting Excel\n",
    "\n",
    "Start by opening Excel, in this case we will give the instance the name 'excel'. Feel free to give this any name you want, as long as you consistently use it when addressing it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "excel = Excel()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Adding data\n",
    "\n",
    "Let us add some data by writing some cells. We will fill the first 5 rows with random data using different methods. We can use Automagica activities to generate the data, but this can be any data ofcourse. \n",
    "\n",
    "A random name can be generated by calling:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can start by giving the first column the heading \"Names\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to cell A1, this is column 1, row 1\n",
    "excel.write_cell(1, 1, \"Name\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Give the second column the heading \"Address\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to cell, B1, this is column 2, row 1\n",
    "excel.write_cell(2, 1, \"Address\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The third column gets the heading \"Age\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to cell, B1, this is column 3, row 1\n",
    "excel.write_cell(3, 1, \"Company\")"
   ]
  },
  {
   "attachments": {
    "excel1.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The worksheet should now look like this:\n",
    "\n",
    "![excel1.png](attachment:excel1.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method 1: Write every cell individually\n",
    "\n",
    "We can write each cell individually:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to cell A2, this is column 1, row 2\n",
    "excel.write_cell(1, 2, generate_random_name())\n",
    "\n",
    "# Write to cell A3, this is column 1, row 3\n",
    "excel.write_cell(1, 3, generate_random_name())\n",
    "\n",
    "# Write to cell A4, this is column 1, row 4\n",
    "excel.write_cell(1, 4, generate_random_name())\n",
    "\n",
    "# Write to cell A5, this is column 1, row 5\n",
    "excel.write_cell(1, 5, generate_random_name())\n",
    "\n",
    "# Write to cell A6, this is column 1, row 6\n",
    "excel.write_cell(1, 6, generate_random_name())"
   ]
  },
  {
   "attachments": {
    "excel2.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The contents of the first cells of the sheet should like something like this:\n",
    "\n",
    "![excel2.png](attachment:excel2.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method 2: Use a for loop to write cells\n",
    "\n",
    "We can loop over the cells of colunm B to fill in random adresses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to cells B2, B3, B4, B5 and B6. This is row 2, cells 2 to 6\n",
    "for i in range(2,7):\n",
    "    excel.write_cell(2,i,generate_random_address())"
   ]
  },
  {
   "attachments": {
    "excel3.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will result in a worksheet comparable to:\n",
    "\n",
    "![excel3.png](attachment:excel3.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method 3: Use Automagica range \n",
    "\n",
    "We can write multiple cells by using the Automagica built-in write_range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Write to cell range C2:C6. This is row 3, cells 2 to 6\n",
    "excel.write_range('C2:C6', \"Example Company\")"
   ]
  },
  {
   "attachments": {
    "excel4.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This will result in:\n",
    "\n",
    "![excel4.png](attachment:excel4.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving Data\n",
    "\n",
    "As a next step we can save the data and and exit Excel.\n",
    "\n",
    "We first declare a path using the Automagica built-in home_path function to make sure we know where it is saved"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare path to save it to, in this case in the homedir with the name \"awesome_excel.xlsx\"\n",
    "excel_save_path = home_path('awesome_excel.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Save the worksheet, by default this is in the homedir\n",
    "excel.save_as(excel_save_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now exit Excel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "excel.quit()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a last stap we can re-open the file we just saved to verify:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C:\\\\Users\\\\TvT\\\\awesome_excel.xlsx'"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "open_file(excel_save_path)"
   ]
  }
 ],
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